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The descent polynomial of a finite $I\subseteq \mathbb{Z}^+$ is the polynomial $d(I,n)$, for which the evaluation at $n>\max(I)$ is the number of permutations on $n$ elements, such that $I$ is the set of indices where the permutation is…

Combinatorics · Mathematics 2019-01-16 Ferenc Bencs

We prove optimal bounds for the convergence rate of ordinal embedding (also known as non-metric multidimensional scaling) in the 1-dimensional case. The examples witnessing optimality of our bounds arise from a result in additive number…

Statistics Theory · Mathematics 2019-05-01 Jordan S. Ellenberg , Lalit Jain

We study approximation of the embedding $\ell_p^m \hookrightarrow \ell_q^m$, $1 \leq p < q \leq \infty$, based on randomized algorithms that use up to $n$ arbitrary linear functionals as information on a problem instance where $n \ll m$. By…

Numerical Analysis · Mathematics 2025-09-22 Robert J. Kunsch , Marcin Wnuk

In this paper we establish exact order estimates for the best uniform orthogonal trigonometric approximations of the classes of $2\pi$-periodic functions, whose $(\psi,\beta)$-derivatives belong to unit balls of spaces $L_{p}$, $1\leq…

Classical Analysis and ODEs · Mathematics 2018-12-18 Tetiana Stepanyuk

We present an efficient framework for solving algebraically-constrained global non-convex polynomial optimization problems over subsets of the hypercube. We prove the existence of an equivalent nonlinear reformulation of such problems that…

Optimization and Control · Mathematics 2024-09-05 Mitchell Tong Harris , Pierre-David Letourneau , Dalton Jones , M. Harper Langston

In approximation of functions based on point values, least-squares methods provide more stability than interpolation, at the expense of increasing the sampling budget. We show that near-optimal approximation error can nevertheless be…

Numerical Analysis · Mathematics 2024-02-14 Abdellah Chkifa , Matthieu Dolbeault

This paper describes a novel method to approximate the polynomial coefficients of regression functions, with particular interest on multi-dimensional classification. The derivation is simple, and offers a fast, robust classification…

Machine Learning · Statistics 2012-03-27 Péter Kövesárki

Polynomial meshes (called sometimes "norming sets") allow us to estimate the supremum norm of polynomials on a fixed compact set by the norm on its discrete subset. We give a general construction of polynomial weakly admissible meshes on…

Numerical Analysis · Mathematics 2025-01-22 Leokadia Bialas-Ciez , Agnieszka Kowalska , Alvise Sommariva

We explore an algorithm for approximating roots of integers, discuss its motivation and derivation, and analyze its convergence rates with varying parameters and inputs. We also perform comparisons with established methods for approximating…

Numerical Analysis · Mathematics 2021-01-11 William Gerst

We study nonstationary dynamical systems formed by sequential concatenation of nonuniformly expanding maps with a uniformly expanding first return map. Assuming a polynomially decaying upper bound on the tails of first return times that is…

Dynamical Systems · Mathematics 2025-09-22 A. Korepanov , J. Leppänen

Let $N$ be a positive integer and let $S_N$ be the set of polynomials with integer coefficients, degree less than $N$, and minimal positive integral over $[0,1]$. D. Bazzanella initiated the study of $S_N$ because of its relation to the…

Number Theory · Mathematics 2026-04-17 Alice Bazzanella , Carlo Sanna

In a previous paper with the same title, we gave an upper bound for the exponent of uniform rational approximation to a quadruple of $\mathbb{Q}$-linearly independent real numbers in geometric progression. Here, we explain why this upper…

Number Theory · Mathematics 2025-04-29 Damien Roy

The paper deals with polynomial interpolation, least-square approximation and cubature of functions defined on the rectangular cylinder, $K=D\times [-1,1]$, with $D$ the unit disk. The nodes used for these processes are the {\it Approximate…

Numerical Analysis · Mathematics 2011-10-26 Stefano De Marchi

We give a highly efficient "semi-agnostic" algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let $p$ be an arbitrary distribution over an interval $I$ which is…

Machine Learning · Computer Science 2013-05-15 Siu-On Chan , Ilias Diakonikolas , Rocco A. Servedio , Xiaorui Sun

This paper studies best finitely supported approximations of one-dimensional probability measures with respect to the $L^r$-Kantorovich (or transport) distance, where either the locations or the weights of the approximations' atoms are…

Probability · Mathematics 2019-03-06 Chuang Xu , Arno Berger

We prove that for any norm |*| in the d-dimensional real vector space V and for any odd n>0 there is a non-negative polynomial p(x), x in V of degree 2n such that p^{1/2n}(x) < |x| < c(n,d) p^{1/2n}(x), where c(n,d)={n+d-1 choose n}^{1/2n}.…

Functional Analysis · Mathematics 2007-05-23 Alexander Barvinok

In this paper we provide explicit upper and lower bounds on certain $L^2$ $n$-widths, i.e., best constants in $L^2$ approximation. We further describe a numerical method to compute these $n$-widths approximately, and prove that this method…

Numerical Analysis · Mathematics 2020-09-28 Andrea Bressan , Michael S. Floater , Espen Sande

We present three new approximation algorithms with improved constant ratios for selecting $n$ points in $n$ disks such that the minimum pairwise distance among the points is maximized. (1) A very simple $O(n\log n)$-time algorithm with…

Computational Geometry · Computer Science 2015-03-13 Adrian Dumitrescu , Minghui Jiang

In this paper we study the subset sum problem with real numbers. Starting from the given problem, we formulate a quadratic maximization problem over a polytope, P, which is eventually written as a distance maximization to a fixed point over…

Optimization and Control · Mathematics 2023-10-09 Marius Costandin

The best polynomial approximation and Chebyshev approximation are both important in numerical analysis. In tradition, the best approximation is regarded as more better than the Chebyshev approximation, because it is usually considered in…

Numerical Analysis · Mathematics 2021-11-17 Xiaolong Zhang
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